Watershed-scale changes in terrestrial nitrogen cycling during a period of decreased atmospheric nitrate and sulfur deposition

AbstractRecent reports suggest that decreases in atmospheric nitrogen (N) deposition throughout Europe and North America may have resulted in declining nitrate export in surface waters in recent decades, yet it is unknown if and how terrestrial N cycling was affected. During a period of decreased atmospheric N deposition, we assessed changes in forest N cycling by evaluating trends in tree-ring δ15N values (between 1980 and 2010; n = 20 trees per watershed), stream nitrate yields (between 2000 and 2011), and retention of atmospherically-deposited N (between 2000 and 2011) in the North and South Tributaries (North and South, respectively) of Buck Creek in the Adirondack Mountains, USA. We hypothesized that tree-ring δ15N values would decline following decreases in atmospheric N deposition (after approximately 1995), and that trends in stream nitrate export and retention of atmospherically deposited N would mirror changes in tree-ring δ15N values. Three of the six sampled tree species and the majority of individual trees showed declining linear trends in δ15N for the period 1980–2010; only two individual trees showed increasing trends in δ15N values. From 1980 to 2010, trees in the watersheds of both tributaries displayed long-term declines in tree-ring δ15N values at the watershed scale (R = −0.35 and p = 0.001 in the North and R = −0.37 and p <0.001 in the South). The decreasing δ15N trend in the North was associated with declining stream nitrate concentrations (−0.009 mg N L−1 yr−1, p = 0.02), but no change in the retention of atmospherically deposited N was observed. In contrast, nitrate yields in the South did not exhibit a trend, and the watershed became less retentive of atmospherically deposited N (−7.3% yr−1, p < 0.001). Our δ15N results indicate a change in terrestrial N availability in both watersheds prior to decreases in atmospheric N deposition, suggesting that decreased atmospheric N deposition was not the sole driver of tree-ring δ15N values at these sites. Other factors, such as decreased sulfur deposition, disturbance, long-term successional trends, and/or increasing atmospheric CO2 concentrations, may also influence trends in tree-ring δ15N values. Furthermore, declines in terrestrial N availability inferred from tree-ring δ15N values do not always correspond with decreased stream nitrate export or increased retention of atmospherically deposited N

Appendix B. A full data set with densities per 2 x 2 m plot reported by plant species for three sampling dates.

A full data set with densities per 2 x 2 m plot reported by plant species for three sampling dates

Appendix A. An expanded version of Table 1.

An expanded version of Table 1

Where Is Garlic Mustard? Understanding the Ecological Context for Invasions of \u3ci\u3eAlliaria petiolata\u3c/i\u3e

The invasive plant Alliaria petiolata (garlic mustard) has spread throughout forest understory and edge communities in much of North America, but its persistence, density, and impacts have varied across sites and time. Surveying the literature since 2008, we evaluated both previously proposed and new mechanisms for garlic mustard\u27s invasion success and note how they interact and vary across ecological contexts. We analyzed how and where garlic mustard has been studied and found a lack of multisite and longitudinal studies, as well as regions that may be under- or overstudied, leading to poor representation for understanding and predicting future invasion dynamics. Inconsistencies in how sampling units are scaled and defined can also hamper our understanding of invasive species. We present new conceptual models for garlic mustard invasion from a macrosystems perspective, emphasizing the importance of synergies and feedbacks among mechanisms across spatial and temporal scales to produce variable ecological contexts

Erythritol, at insecticidal doses, has harmful effects on two common agricultural crop plants

<div><p>Erythritol, a non-nutritive polyol, is the main component of the artificial sweetener Truvia^<b>®</b>. Recent research has indicated that erythritol may have potential as an organic insecticide, given its harmful effects on several insects but apparent safety for mammals. However, for erythritol to have practical use as an insecticide in agricultural settings, it must have neutral to positive effects on crop plants and other non-target organisms. We examined the dose-dependent effects of erythritol (0, 5, 50, 500, 1000, and 2000 mM) on corn (<i>Zea mays</i>) and tomato (<i>Solanum lycopersicum</i>) seedling growth and seed germination. Erythritol caused significant reductions in both belowground (root) and aboveground (shoot) dry weight at and above the typical minimum insecticidal dose (500 mM erythritol) in tomato plants, but not in corn plants. Both corn and tomato seed germination was inhibited by erythritol but the tomato seeds appeared to be more sensitive, responding at concentrations as low as 50 mM erythritol (in contrast to a minimum damaging dose of 1000 mM erythritol for corn seeds). Our results suggest erythritol may have damaging non-target effects on certain plant crops when used daily at the typical doses needed to kill insect pests. Furthermore, if erythritol’s damaging effects extend to certain weed species, it also may have potential as an organic herbicide.</p></div

Seedling growth (measured as dry weight) and seed germination of corn and tomato exposed to 5 different erythritol treatments and a deionized water control.

<p>Dry weight: n = 11 replicates per treatment group for each species; seed germination: n = 3 replicate petri dishes (with 4 seeds per petri dish) per treatment group for each species.</p

Developing a Flexible Learning Activity on Biodiversity and Spatial Scale Concepts Using Open-Access Vegetation Datasets from the National Ecological Observatory Network

Biodiversity is a complex, yet essential, concept for undergraduate students in ecology and other natural sciences to grasp. As beginner scientists, students must learn to recognize, describe, and interpret patterns of biodiversity across various spatial scales and understand their relationships with ecological processes and human influences. It is also increasingly important for undergraduate programs in ecology and related disciplines to provide students with experiences working with large ecological datasets to develop students’ data science skills and their ability to consider how ecological processes that operate at broader spatial scales (macroscale) affect local ecosystems. To support the goals of improving student understanding of macroscale ecology and biodiversity at multiple spatial scales, we formed an interdisciplinary team that included grant personnel, scientists, and faculty from ecology and spatial sciences to design a flexible learning activity to teach macroscale biodiversity concepts using large datasets from the National Ecological Observatory Network (NEON). We piloted this learning activity in six courses enrolling a total of 109 students, ranging from midlevel ecology and GIS/remote sensing courses, to upper-level conservation biology. Using our classroom experiences and a pre/postassessment framework, we evaluated whether our learning activity resulted in increased student understanding of macroscale ecology and biodiversity concepts and increased familiarity with analysis techniques, software programs, and large spatio-ecological datasets. Overall, results suggest that our learning activity improved student understanding of biological diversity, biodiversity metrics, and patterns of biodiversity across several spatial scales. Participating faculty reflected on what went well and what would benefit from changes, and we offer suggestions for implementation of the learning activity based on this feedback. This learning activity introduced students to macroscale ecology and built student skills in working with big data (i.e., large datasets) and performing basic quantitative analyses, skills that are essential for the next generation of ecologists

Erythritol delays seed germination in corn.

<p>Mean (± 1 SE) number of days to seed germination for A) corn and B) tomato over 18 days at 6 different treatment concentrations of erythritol. For each species, seeds were treated in petri dishes (4 seeds per dish; 3 dishes per treatment group) and the mean days to germination was calculated for each petri dish. Note that no seeds germinated in the 2000 mM treatment group for corn and the 500 mM, 1000 mM, and 2000 mM treatment groups for tomato, so these treatment groups were not included in the analysis. Means with the same letter are not significantly different from each other (Tukey HSD test, p < 0.05).</p

Erythritol reduces tomato dry weight, but has no effect on corn dry weight.

<p>Mean (± 1 SE) root and shoot dry weight (biomass) for A) corn and B) tomato seedlings treated with erythritol spray at 6 different concentrations for 21 days (corn) or 28 days (tomato). There were 11 plants of each species per erythritol treatment group. Means with the same letter within a response variable are not significantly different from each other (Tukey HSD test, p < 0.05).</p

Erythritol causes dose-dependent inhibition of seed germination in corn and tomato.

<p>Median (IQR) A) corn and B) tomato seed percent germination over 18 days at 6 different treatment concentrations of erythritol. For each species, seeds were treated in petri dishes (4 seeds per dish; 3 dishes per treatment group) and the percent germination was calculated for each petri dish. Medians with the same letter are not significantly different from each other (Mann-Whitney U test, p < 0.05).</p